Can randomized control trials reduce poverty?

If you give milk to schoolchildren and they perform well in school, how do you know it’s because of the milk, or because the children were high achievers anyway, or went to better schools?

By randomly choosing the children who receive the milk, and comparing the outcomes of this “treatment group” with a “control group” (those that didn’t receive milk), we can get a more accurate measure of the program’s impact than if we were to simply compare the children’s performance before and after they drank milk.

In a recent issue of Boston Review[1], Rachel Glennerster and Michael Kremer, two of the leading proponents of these randomized control trials (RCTs), survey what we have learned from them, especially those that show that people sometimes deviate from standard economic assumptions (a burgeoning field known as “behavioral economics”).

At Michael’s and Rachel’s request, Jishnu Das, Jeff Hammer and I wrote a comment, the more complete version of which is here[2]. We make two points:

RCTs tell us what will happen if you intervene; they don’t answer the question: “Should you intervene?” The answer lies in whether there is a market failure or need for redistribution and, in the latter case especially, whether giving milk to schoolchildren is the best way to improve the welfare of poor people.

Even if there is a rationale for intervention, RCTs—which are usually implemented by an NGO that manages a well-defined program—tell us very little about what will happen if the program is implemented by real government officials who are facing political pressures and may not be able to (or even want to) ensure that milk is actually delivered to the children.

Randomized control trials have become the most popular technique in development economics. Let’s make sure they can be used to contribute to development’s goal—to improve the lives of the world’s poor.